The convex optimization approach to regret minimization
نویسنده
چکیده
A well studied and general setting for prediction and decision making is regret minimization in games. Recently the design of algorithms in this setting has been influenced by tools from convex optimization. In this chapter we describe the recent framework of online convex optimization which naturally merges optimization and regret minimization. We describe the basic algorithms and tools at the heart of this framework, which have led to the resolution of fundamental questions of learning in games.
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تاریخ انتشار 2011